scholarly journals Identifying Diurnal Variability of Brain Connectivity Patterns Using Graph Theory

2021 ◽  
Vol 11 (1) ◽  
pp. 111
Author(s):  
Farzad V. Farahani ◽  
Magdalena Fafrowicz ◽  
Waldemar Karwowski ◽  
Bartosz Bohaterewicz ◽  
Anna Maria Sobczak ◽  
...  
Keyword(s):  
Resting State ◽  
Network Architecture ◽  
Inferior Frontal Gyrus ◽  
Brain Network ◽  
Time Of Day ◽  
Precentral Gyrus ◽  
Network Organization ◽  
Diurnal Variability ◽  
Sleep Inertia ◽  
Brain Functions

Significant differences exist in human brain functions affected by time of day and by people’s diurnal preferences (chronotypes) that are rarely considered in brain studies. In the current study, using network neuroscience and resting-state functional MRI (rs-fMRI) data, we examined the effect of both time of day and the individual’s chronotype on whole-brain network organization. In this regard, 62 participants (39 women; mean age: 23.97 ± 3.26 years; half morning- versus half evening-type) were scanned about 1 and 10 h after wake-up time for morning and evening sessions, respectively. We found evidence for a time-of-day effect on connectivity profiles but not for the effect of chronotype. Compared with the morning session, we found relatively higher small-worldness (an index that represents more efficient network organization) in the evening session, which suggests the dominance of sleep inertia over the circadian and homeostatic processes in the first hours after waking. Furthermore, local graph measures were changed, predominantly across the left hemisphere, in areas such as the precentral gyrus, putamen, inferior frontal gyrus (orbital part), inferior temporal gyrus, as well as the bilateral cerebellum. These findings show the variability of the functional neural network architecture during the day and improve our understanding of the role of time of day in resting-state functional networks.

scholarly journals A whole-brain and cross-diagnostic perspective on functional brain network dysfunction

2018 ◽  
Author(s):  
Marjolein Spronk ◽  
Kaustubh Kulkarni ◽  
Jie Lisa Ji ◽  
Brian P. Keane ◽  
Alan Anticevic ◽  
...  
Keyword(s):  
Mental Illness ◽  
Resting State ◽  
Brain Network ◽  
Functional Network ◽  
Graph Distance ◽  
Network Organization ◽  
Whole Brain ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Mental Diseases

AbstractA wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations have seemed to support various theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in broad, whole-brain perspective. Using a graph distance measure – connectome-wide correlation – we found that whole-brain resting-state functional network organization in humans is highly similar across a variety of mental diseases and healthy controls. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease those differences are informative. Such small network alterations may reflect the fact that most psychiatric patients maintain overall cognitive abilities similar to those of healthy individuals (relative to, e.g., the most severe schizophrenia cases), such that whole-brain functional network organization is expected to differ only subtly even for mental diseases with devastating effects on everyday life. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases.

Altered brain network organization in romantic love as measured with resting-state fMRI and graph theory

2020 ◽  
Vol 14 (6) ◽  
pp. 2771-2784 ◽  
Author(s):  
Chuan Wang ◽  
Sensen Song ◽  
Federico d’Oleire Uquillas ◽  
Anna Zilverstand ◽  
Hongwen Song ◽  
...  
Keyword(s):  
Graph Theory ◽  
Resting State ◽  
Romantic Love ◽  
Resting State Fmri ◽  
Brain Network ◽  
Network Organization

scholarly journals Ballroom Dancing Promotes Neural Activity in the Sensorimotor System: A Resting-State fMRI Study

2018 ◽  
Vol 2018 ◽  
pp. 1-7 ◽  
Author(s):  
Yingzhi Lu ◽  
Qi Zhao ◽  
Yingying Wang ◽  
Chenglin Zhou
Keyword(s):  
Functional Connectivity ◽  
Neural Activity ◽  
Resting State ◽  
Inferior Frontal Gyrus ◽  
Middle Temporal Gyrus ◽  
Sensorimotor System ◽  
Precentral Gyrus ◽  
Action Perception ◽  
Ballroom Dancing ◽  
Left Middle

Objective. This study aims at investigating differences in the spontaneous brain activity and functional connectivity in the sensorimotor system between ballroom dancers and nondancers, to further support the functional alteration in people with expertise. Materials and Methods. Twenty-three ballroom dancers and twenty-one matched novices with no dance experience were recruited in this study. Amplitude of low-frequency fluctuation (ALFF) and seed-based functional connectivity, as methods for assessing resting-state functional magnetic resonance imaging (rs-fMRI) data, were used to reveal the resting-state brain function in these participants. Results. Compared to the novices, ballroom dancers showed increased ALFF in the left middle temporal gyrus, bilateral precentral gyrus, bilateral inferior frontal gyrus, left postcentral gyrus, left inferior temporal gyrus, right middle occipital gyrus, right superior temporal gyrus, and left middle frontal gyrus. The ballroom dancers also demonstrated lower ALFF in the left lingual gyrus and altered functional connectivity between the inferior frontal gyrus and temporal, parietal regions. Conclusions. Our results indicated that ballroom dancers showed elevated neural activity in sensorimotor regions relative to novices and functional alterations in frontal-temporal and frontal-parietal connectivity, which may reflect specific training experience related to ballroom dancing, including high-capacity action perception, attentional control, and movement adjustment.

scholarly journals Changes in resting-state measures of prostate cancer patients exposed to androgen deprivation therapy

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Julio Plata-Bello ◽  
Ana Plata-Bello ◽  
Yaiza Pérez-Martín ◽  
David López-Curtis ◽  
Silvia Acosta-López ◽  
...  
Keyword(s):  
Androgen Deprivation Therapy ◽  
Resting State ◽  
Inferior Frontal Gyrus ◽  
Low Frequency ◽  
Region Of Interest ◽  
Androgen Deprivation ◽  
Receptor Expression ◽  
Control Group ◽  
Precentral Gyrus ◽  
The Right

AbstractThe aim of the present work is to describe the differences in rs-fMRI measures (Amplitude of low frequency fluctuations [ALFF], Regional Homogeneity [ReHo] and Functional Connectivity [FC]) between patients exposed to Androgen deprivation therapy (ADT) and a control group. Forty-nine ADT patients and fifteen PC-non-ADT patients (Controls) were included in the study. A neuropsychological evaluation and a resting-state fMRI was performed to evaluate differences in ALFF and ReHo. Region of interest (ROI) analysis was also performed. ROIs were selected among those whose androgen receptor expression (at RNA-level) was the highest. FC analysis was performed using the same ROIs. Higher ALFF in frontal regions and temporal regions was identified in Controls than in ADT patients. In the ROI analysis, higher activity for Controls than ADT patients was shown in the left inferior frontal gyrus and in the left precentral gyrus. Lower ALFF in the right hippocampus and the lateral geniculate nucleus of the right thalamus was identified for Controls than ADT patients. Higher ReHo was observed in Controls in the left parietal-occipital area. Finally, ADT patients presented an increase of FC in more regions than Controls. These differences may reflect an impairment in brain functioning in ADT users.

scholarly journals Alteration of Whole Brain ALFF/fALFF and Degree Centrality in Adolescents With Depression and Suicidal Ideation After Electroconvulsive Therapy: A Resting-State fMRI Study

2021 ◽  
Vol 15 ◽  
Author(s):  
Xiao Li ◽  
Renqiang Yu ◽  
Qian Huang ◽  
Xiaolu Chen ◽  
Ming Ai ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Electroconvulsive Therapy ◽  
Resting State ◽  
Suicide Ideation ◽  
Inferior Frontal Gyrus ◽  
Degree Centrality ◽  
Hamilton Depression Scale ◽  
Precentral Gyrus ◽  
Left Hippocampus ◽  
The Right

Major depressive disorder (MDD) is one of the most widespread mental disorders and can result in suicide. Suicidal ideation (SI) is strongly predictive of death by suicide, and electroconvulsive therapy (ECT) is effective for MDD, especially in patients with SI. In the present study, we aimed to determine differences in resting-state functional magnetic resonance imaging (rs-fMRI) in 14 adolescents aged 12–17 with MDD and SI at baseline and after ECT. All participants were administered the Hamilton Depression Scale (HAMD) and Beck Scale for Suicide Ideation (BSSI) and received rs-fMRI scans at baseline and after ECT. Following ECT, the amplitude of low frequency fluctuation (ALFF) and fractional ALFF (fALFF) significantly decreased in the right precentral gyrus, and the degree centrality (DC) decreased in the left triangular part of the inferior frontal gyrus and increased in the left hippocampus. There were significant negative correlations between the change of HAMD (ΔHAMD) and ALFF in the right precentral gyrus at baseline, and between the change of BSSI and the change of fALFF in the right precentral gyrus. The ΔHAMD was positively correlated with the DC value of the left hippocampus at baseline. We suggest that these brain regions may be indicators of response to ECT in adolescents with MDD and SI.

scholarly journals A Whole-Brain and Cross-Diagnostic Perspective on Functional Brain Network Dysfunction

2020 ◽  
Vol 31 (1) ◽  
pp. 547-561
Author(s):  
Marjolein Spronk ◽  
Brian P Keane ◽  
Takuya Ito ◽  
Kaustubh Kulkarni ◽  
Jie Lisa Ji ◽  
...  
Keyword(s):  
Mental Illness ◽  
Mental Disorders ◽  
Resting State ◽  
Brain Network ◽  
Graph Distance ◽  
Network Organization ◽  
Whole Brain ◽  
Functional Brain ◽  
Functional Brain Network ◽  
Mental Diseases

Abstract A wide variety of mental disorders have been associated with resting-state functional network alterations, which are thought to contribute to the cognitive changes underlying mental illness. These observations appear to support theories postulating large-scale disruptions of brain systems in mental illness. However, existing approaches isolate differences in network organization without putting those differences in a broad, whole-brain perspective. Using a graph distance approach—connectome-wide similarity—we found that whole-brain resting-state functional network organization is highly similar across groups of individuals with and without a variety of mental diseases. This similarity was observed across autism spectrum disorder, attention-deficit hyperactivity disorder, and schizophrenia. Nonetheless, subtle differences in network graph distance were predictive of diagnosis, suggesting that while functional connectomes differ little across health and disease, those differences are informative. These results suggest a need to reevaluate neurocognitive theories of mental illness, with a role for subtle functional brain network changes in the production of an array of mental diseases. Such small network alterations suggest the possibility that small, well-targeted alterations to brain network organization may provide meaningful improvements for a variety of mental disorders.

scholarly journals Progressive reconfiguration of resting-state brain networks as psychosis develops: Preliminary results from the North American Prodrome Longitudinal Study (NAPLS) consortium

2017 ◽  
Author(s):  
Hengyi Cao ◽  
Yoonho Chung ◽  
Sarah C. McEwen ◽  
Carrie E. Bearden ◽  
Jean Addington ◽  
...  
Keyword(s):  
Longitudinal Study ◽  
North American ◽  
Resting State ◽  
Network Architecture ◽  
Brain Networks ◽  
Brain Network ◽  
Network Efficiency ◽  
The North ◽  
Network Diversity ◽  
Global Efficiency

AbstractMounting evidence has shown disrupted brain network architecture across the psychosis spectrum. However, whether these changes relate to the development of psychosis is unclear. Here, we used graph theoretical analysis to investigate longitudinal changes in resting-state brain networks in samples of 72 subjects at clinical high risk (including 8 cases who converted to full psychosis) and 48 healthy controls drawn from the North American Prodrome Longitudinal Study (NAPLS) consortium. We observed progressive reduction in global efficiency (P = 0.006) and increase in network diversity (P = 0.001) in converters compared with non-converters and controls. More refined analysis separating nodes into nine key brain networks demonstrated that these alterations were primarily driven by progressively diminished local efficiency in the default-mode network (P = 0.004) and progressively enhanced node diversity across all networks (P < 0.05). The change rates of network efficiency and network diversity were significantly correlated (P = 0.003), suggesting these changes may reflect shared underlying neural mechanisms. In addition, change rates of global efficiency and node diversity were significantly correlated with change rate of cortical thinning in the prefrontal cortex in converters (P < 0.03) and could be predicted by visuospatial memory scores at baseline (P < 0.04). These results provide preliminary evidence for longitudinal reconfiguration of resting-state brain networks during psychosis development and suggest that decreased network efficiency, reflecting an increase in path length between nodes, and increased network diversity, reflecting a decrease in the consistency of functional network organization, are implicated in the progression to full psychosis.

scholarly journals Latent functional connectivity underlying multiple brain states

2021 ◽  
Author(s):  
Ethan M McCormick ◽  
Katelyn L Arnemann ◽  
Takuya Ito ◽  
Stephen Jose Hanson ◽  
Michael W Cole
Keyword(s):  
Functional Connectivity ◽  
Resting State ◽  
Network Architecture ◽  
Brain Activity ◽  
Brain Network ◽  
Mathematical Framework ◽  
Human Connectome Project ◽  
Brain States ◽  
Task Conditions ◽  
Psychometric G

Functional connectivity (FC) studies have predominantly focused on resting state, where ongoing dynamics are thought to primarily reflect the brain's intrinsic network architecture, which is thought to be broadly relevant to brain function because it persists across brain states. However, it is unknown whether resting state is the optimal state for measuring intrinsic FC. We propose that latent FC, reflecting patterns of connectivity shared across many brain states, may better capture intrinsic FC relative to measures derived from resting state alone. We estimated latent FC in relation to 7 highly distinct task states (24 task conditions) and resting state using fMRI data from 352 participants from the Human Connectome Project. Latent FC was estimated independently for each connection by applying leave-one-task-out factor analysis on the state FC estimates. Compared to resting-state connectivity, we found that latent connectivity improves generalization to held-out brain states, better explaining patterns of both connectivity and task-evoked brain activity. We also found that latent connectivity improved prediction of behavior, measured by the general intelligence factor psychometric g. Our results suggest that patterns of FC shared across many brain states, rather than just resting state, better reflects general, state-independent connectivity. This affirms the notion of "intrinsic" brain network architecture as a set of connectivity properties persistent across brain states, providing an updated conceptual and mathematical framework of intrinsic connectivity as a latent factor.

scholarly journals Lateralized Resting-State Functional Brain Network Organization Changes in Heart Failure

PLoS ONE ◽  
2016 ◽  
Vol 11 (5) ◽  
pp. e0155894 ◽  
Author(s):  
Bumhee Park ◽  
Bhaswati Roy ◽  
Mary A. Woo ◽  
Jose A. Palomares ◽  
Gregg C. Fonarow ◽  
...  
Keyword(s):  
Heart Failure ◽  
Resting State ◽  
Brain Network ◽  
Network Organization ◽  
Functional Brain ◽  
Functional Brain Network

Task-linked Diurnal Brain Network Reorganization in Older Adults: A Graph Theoretical Approach

2017 ◽  
Vol 29 (3) ◽  
pp. 560-572 ◽  
Author(s):  
John A. E. Anderson ◽  
Saman Sarraf ◽  
Tarek Amer ◽  
Buddhika Bellana ◽  
Vincent Man ◽  
...  
Keyword(s):  
Older Adults ◽  
Young Adults ◽  
Brain Activity ◽  
Brain Network ◽  
Time Of Day ◽  
Network Organization ◽  
Graph Metrics ◽  
Graph Metric ◽  
Graph Theoretical Approach ◽  
Brain Network Reorganization

Testing older adults in the morning generally improves behavioral performance relative to afternoon testing. Morning testing is also associated with brain activity similar to that of young adults. Here, we used graph theory to explore how time of day (TOD) affects the organization of brain networks in older adults across rest and task states. We used nodes from the automated anatomical labeling atlas to construct participant-specific correlation matrices of fMRI data obtained during 1-back tasks with interference and rest. We computed pairwise group differences for key graph metrics, including small-worldness and modularity. We found that older adults tested in the morning and young adults did not differ on any graph metric. Both of these groups differed from older adults tested in the afternoon during the tasks—but not rest. Specifically, the latter group had lower modularity and small-worldness (indices of more efficient network organization). Across all groups, higher modularity and small-worldness strongly correlated with reduced distractibility on an implicit priming task. Increasingly, TOD is seen as important for interpreting and reproducing neuroimaging results. Our study emphasizes how TOD affects brain network organization and executive control in older adults.

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